Although plenty of techniques have been proposed [1]}, SAR image change detection is a still challenging task. Image quality is deteriorated by speckle noise which hinders the meticulous interpretation of SAR data. Many methods are implemented to address the issue of speckle noise. They are usually comprised of three steps: 1) image coregistration, 2) difference image (DI) generation, and 3) DI classification [2]}. Image coregistration is a fundamental task to establish the spatial correspondences between multitemporal SAR images. In the second step, the DI is commonly generated by the log-ratio, Gauss-ratio [3]}, and neighborhood-ratio [4]} operators. For the DI classification step, most researches are devoted to building a robust classifier. It is a non-trivial task since a powerful classifier directly determines the precision of change detection.
